Extended Abstract
Background and Purpose
In the past two decades, mechanisms underlying athletic expertise have garnered increasing attention from researchers. Elite sports performance relies not only on physical abilities but also on efficient visual information processing and rapid decision-making. Visual search strategies, involving eye movements such as fixations and saccades, enable athletes to anticipate and respond to dynamic environmental cues. Previous research has shown differences in gaze behavior between athletes and non-athletes. Most studies have focused on real-game situations, making it difficult to separate the effects of general sports experience from task-specific knowledge. To address this research gap, dynamic, standardized, non-sport-specific visual tasks can be used to examine fundamental gaze behavior under controlled conditions. Therefore, the purpose of this study was to compare key gaze behavior indices, including the number of fixations, the number of saccades, and fixation duration, between athlete and non-athlete students during a controlled dynamic visual tracking task using eye-tracking technology.
Methods
This study, adhering to ethical research guidelines, utilized a causal-comparative design to compare visual search indices (number of fixations, saccades, and fixation duration) between athletes and non-athletes. The sample included 89 students, with 45 athletes and 44 non-athletes, selected through convenience sampling. In an orientation session, the purpose and procedures of the study were explained. Demographic data (age, gender, type of sport) were collected via questionnaire. Visual acuity was verified using a Snellen chart, ensuring normal vision for all participants. Eye movements were recorded using the EyeLink 1000 Plus device at a sampling rate of 500 Hz. Participants were seated 70 cm from the display, with chins stabilized to minimize head movement. A 25-mm lens camera was positioned 45 cm away. The research protocol was designed using Experiment Builder in three stages: first, a 9-point calibration, followed by validation, and then a 20-second dynamic visual task, which was created in Blender 4.3.2. The task involved a point-shaped visual target with an angular size of 0.775 degrees, moving horizontally in a regular triangular wave pattern at five velocities (20–100 degrees/second). Participants tracked the target without prior training, and the eye-tracking task took less than five minutes for each individual. Eye-tracking data were analyzed using DataViewer software. Fixations (threshold: 100–700 ms) and saccades (minimum angular velocity: 30 degrees/second) were extracted, with blinks and incomplete data excluded. Data normality was assessed using the Shapiro–Wilk test, and variance homogeneity was evaluated with Levene's test. Independent t-tests were applied for normally distributed data, and Mann–Whitney U tests for non-normally distributed data. All statistical analyses were conducted in SPSS 26 with a significance level of 0.05.
Results
This study investigated visual search indices (fixations, saccades, fixation duration) in 89 students (45 athletes, 44 non-athletes) during dynamic visual tracking. Athlete (21.78 ± 1.56 years) and non-athlete (21.43 ± 1.95 years) groups were similarly aged; among athletes, 64.4% participated in ball sports and 35.6% in non-ball sports. Athletes exhibited fewer saccades (M = 22.63 vs. 28.36) and fixations (M = 13.57 vs. 18.25) than non-athletes; fixation duration was slightly shorter in athletes (344.25 ms vs. 352.01 ms). Shapiro–Wilk tests indicated normality in non-athletes for all variables (p ≥ 0.05), whereas athletes showed non-normal distributions for saccade (p = 0.017) and fixation counts (p = 0.015), though fixation duration was normal (p = 0.448). Accordingly, Mann–Whitney U tests revealed significantly fewer saccades (p = 0.003) and fixations (p = 0.002) in athletes (mean ranks: 36.83 and 36.80) versus non-athletes (53.35 and 53.39). An independent t-test with corrected variance (F = 4.898, p = 0.030) showed no significant difference in fixation duration (t = 0.697, p = 0.488). Heatmaps weighted by fixation count revealed athletes displayed more uniform, targeted gaze patterns focused on direction-change points with fewer fixations on straight segments (40–100°/s), whereas non-athletes showed dispersed gaze across the entire path, indicating athletes' superior motion tracking and prediction. Supplemental analysis comparing ball versus non-ball sport athletes found non-significant differences in saccades (p = 0.176), fixations (p = 0.213), and fixation duration (p = 0.052), though ball-sport athletes showed numerically higher saccade and fixation counts. These patterns may reflect sport-type-specific visual strategies requiring further investigation.
Conclusion
This study compared gaze behavior between athletes and non-athletes during dynamic visual tracking. Athletes executed significantly fewer saccades and fixations than non-athletes, whose more dispersed eye movements reflected less efficient visual search. Fixation duration did not differ between groups, likely due to the task's simplicity reducing the need for gaze adjustments. These findings indicate that gaze differences reflect distinct visual strategies rather than performance disparities. Exploratory analysis revealed no significant differences between ball and non-ball sport athletes in saccades, fixations, or fixation duration, warranting further investigation. Results demonstrate that group differences in gaze behavior emerge even in simplified, non-sport-specific tasks, supporting controlled dynamic paradigms for examining eye movement tendencies. Future research should complement these basic assessments with complex, sport-realistic tasks to comprehensively understand visual strategies.

Article Message
This study shows that athletes and non-athletes differ in their eye movement patterns even during a simple, non-sport tracking task, with athletes making fewer saccades and fixations. The findings of this study emphasize the effectiveness of controlled dynamic visual tasks in identifying visual search strategies and provide a methodological framework for future research in this area.
Funding
This work has been financially supported by Shahid Rajaee Teacher Training University Fund under grant number 1404/379004.
Ethical Considerations
This research was conducted in accordance with research guidelines and adheres to all ethical principles.
Authors' Contributions
The authors have made equal contributions in the design, implementation, and writing of various sections of the research.
Conflict of Interest
The authors declare no conflict of interest.
Acknowledgments
We sincerely thank the Vice President for Research and Technology, especially the technical staff who collaborated in the eye tracking training and working with the device. We also thank all the participants for their time and participation.